aminghadersohi commented on code in PR #36553:
URL: https://github.com/apache/superset/pull/36553#discussion_r2895040710
##########
superset/core/mcp/core_mcp_injection.py:
##########
@@ -85,11 +89,18 @@ def decorator(func: F) -> F:
name=tool_name,
description=tool_description,
tags=tool_tags,
+ task=task,
)
mcp.add_tool(tool)
+ task_status = "background-task" if task else "sync"
Review Comment:
Good observation about the logging accuracy. The task_status computed from
the task object might not reflect the actual registration outcome if a fallback
changed the behavior. I'll fix the logging to use the actual registration
result. Thanks.
##########
superset/mcp_service/dashboard/tool/generate_dashboard.py:
##########
@@ -233,6 +247,7 @@ def generate_dashboard(
)
except Exception as e:
+ await ctx.error("Error creating dashboard: %s" % (str(e),))
logger.error("Error creating dashboard: %s", e)
Review Comment:
Good point — if ctx.error raises, the local logger.error and return won't
execute. I'll reorder to log locally first, then await ctx.error, so we at
least capture the error in our logs regardless. Thanks.
##########
superset-core/src/superset_core/mcp/__init__.py:
##########
@@ -62,13 +63,20 @@ def my_tool(): ...
@tool(name="custom_name", protect=False)
def my_tool(): ...
+ Or with background task support (requires async function):
+ @tool(task=True)
+ async def long_running_tool(): ...
Review Comment:
Ha, yes\! The MCP layer runs in its own async context via FastMCP/Starlette,
so we get to use async there without affecting the synchronous Flask request
handling. It's kind of a nice bridge — the MCP tools themselves use async
internally while calling back into Flask's sync DAOs when needed.
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